Where are the best Insights?

Most of business managers would like to make informative business decisions rationally based on data and evidence, and yet corporate meetings are still too often dominated by “vision” and “gut feeling” arguments. It is easy to argue that uncertainties of the market landscape are impossible to predict, and one never has enough information at any given time. This is a difficult argument to counter, but there are examples that show data driven decisions are possible and they dramatically improve the results, when used properly.

Consider commonly used GPS device/service for your car, that allows you to predict your arrival to the destinations of your choice with a relative accuracy, even when you do not know the directions in advance. Later versions are even capable to route based on current traffic conditions. Think about this as an analogy for providing vital business information to support management decisions. Understanding what makes GPS so indispensable for driving vehicles can provide ideas for design of service indispensable for driving business decisions.

No reasonably accurate position reading is possible without a minimum of three satellite signals. In business environment these “satellite” signals may be Market, Customer and Company data sources. The intersections of Financial, Operational and Customer Satisfaction metrics could provide your product, brand or company its current position reading with relative accuracy. All of these data streams are available either from internal and/or external sources, but the synthesis process of federating the data and its correlation into “objective” metrics is not commonly observed in practice.

The positioning is critical as a starting point, but without availability of cartography the GPS would not be as useful. From the perspective of business, a combination of Customer Intelligence (transaction history, relationship history, satisfaction/loyalty data and utilization analytics), Market (non Customers) and Employees perceptions, form the maps for charting the course of business decisions. Most of this data is available only in unstructured format and therefore largely ignored by many BI/Big Data initiatives.

GPS routing algorithms use Operational (speed), Intelligence (traffic conditions) and Cartography information to suggest available decisions to reach desired destination and to predict likely time of arrival. Use of predictive analytic models is relatively common for investment management, banking and national security. I yet to see them used in product management, marketing or sales operations applications.

There are a lot of layers need to be peeled from that “onion” before any specific, functional solution can be crafted for your organization. The important things to remember are:

You can buy technology tools and data access sources, but you cannot buy the solution for your business. The true solution requires fundamental understanding of your industry, clear comprehension of your marketplace and intimate knowledge of your company. Not too many business practitioners would publicly acknowledge their belief in magic, and yet they keep shopping for the magic bullet.

Predictive models are just that – models. Just like GPS sometimes can suggest a wrong turn, these models cannot guarantee the best decision. However, they can consistently improve quality of management decisions that would translate into consistently better profit margins, earnings per share, or whatever other metric you want to apply. The idea is not to predict the future, but to estimate probabilities of specific outcomes to be realized, based on specific actions and conditions.

Resist the temptation to use the models in autopilot mode – that is the shortest route to disaster. The most recent example of this unfortunate practice in business is the 2008 financial crisis. The best example of such behavior in use of GPS is described Newport-to-Ensenada 2012 race tragedy report. Regardless of the model quality, the decision maker, driver or skipper bear ultimate responsibility for the decision output.

The most valuable insights are hiding near intersection of multiple data sources. Use innovative, holistic thinking to optimize your business processes and practices, instead one-dimensional approach.